Optimal spectrum sensing for cognitive radio network utilizing software defined radio platform

The static spectrum allocation policy in Malaysia and the rapid growth of wireless communication services have led to spectrum scarcity problem. Consequently, the Quality of Service (QoS) for new wireless services might be compromised as most of the radio bands are already assigned to licensed users...

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Main Author:	Tahir, Nurizan
Format:	Thesis
Language:	English
Published:	2018
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/78940/1/NurizanTahirMFKE2018.pdf
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id	my-utm-ep.78940
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spelling	my-utm-ep.789402018-09-19T05:12:39Z Optimal spectrum sensing for cognitive radio network utilizing software defined radio platform 2018-01 Tahir, Nurizan TK Electrical engineering. Electronics Nuclear engineering The static spectrum allocation policy in Malaysia and the rapid growth of wireless communication services have led to spectrum scarcity problem. Consequently, the Quality of Service (QoS) for new wireless services might be compromised as most of the radio bands are already assigned to licensed users. But, the spectrum occupancy’s measurement shows that the allocated spectrum is underutilized. Therefore, in this project, Opportunistic Spectrum Access (OSA) scheme is used to overcome the spectrum scarcity problem. The concept of OSA in cognitive radio technology is used to exploit the spectrum by permitting the secondary user to temporally use the licensed spectrum band when it is free. Hence, spectrum sensing is very important for the secondary user to avoid harmful interference to other wireless services. This project specifically will develop an optimal spectrum sensing mechanism using Particle Swarm Optimization (PSO) algorithm on Software Defined Radio (SDR) using platform called Universal Software Radio Peripheral (USRP). The data has been analysed to validate the performance of the spectrum sensing mechanism referring to the Probability of Detection (Pd) and Probability of False Alarm (Pf). The result shows that the optimal throughput is 93% for Pd 90%, SNR of 1.5dB and Pf 5% which is an improvement of 14% compared with non-optimal method. 2018-01 Thesis http://eprints.utm.my/id/eprint/78940/ http://eprints.utm.my/id/eprint/78940/1/NurizanTahirMFKE2018.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:108364 masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Tahir, Nurizan Optimal spectrum sensing for cognitive radio network utilizing software defined radio platform
description	The static spectrum allocation policy in Malaysia and the rapid growth of wireless communication services have led to spectrum scarcity problem. Consequently, the Quality of Service (QoS) for new wireless services might be compromised as most of the radio bands are already assigned to licensed users. But, the spectrum occupancy’s measurement shows that the allocated spectrum is underutilized. Therefore, in this project, Opportunistic Spectrum Access (OSA) scheme is used to overcome the spectrum scarcity problem. The concept of OSA in cognitive radio technology is used to exploit the spectrum by permitting the secondary user to temporally use the licensed spectrum band when it is free. Hence, spectrum sensing is very important for the secondary user to avoid harmful interference to other wireless services. This project specifically will develop an optimal spectrum sensing mechanism using Particle Swarm Optimization (PSO) algorithm on Software Defined Radio (SDR) using platform called Universal Software Radio Peripheral (USRP). The data has been analysed to validate the performance of the spectrum sensing mechanism referring to the Probability of Detection (Pd) and Probability of False Alarm (Pf). The result shows that the optimal throughput is 93% for Pd 90%, SNR of 1.5dB and Pf 5% which is an improvement of 14% compared with non-optimal method.
format	Thesis
qualification_level	Master's degree
author	Tahir, Nurizan
author_facet	Tahir, Nurizan
author_sort	Tahir, Nurizan
title	Optimal spectrum sensing for cognitive radio network utilizing software defined radio platform
title_short	Optimal spectrum sensing for cognitive radio network utilizing software defined radio platform
title_full	Optimal spectrum sensing for cognitive radio network utilizing software defined radio platform
title_fullStr	Optimal spectrum sensing for cognitive radio network utilizing software defined radio platform
title_full_unstemmed	Optimal spectrum sensing for cognitive radio network utilizing software defined radio platform
title_sort	optimal spectrum sensing for cognitive radio network utilizing software defined radio platform
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2018
url	http://eprints.utm.my/id/eprint/78940/1/NurizanTahirMFKE2018.pdf
_version_	1747818108811214848

Optimal spectrum sensing for cognitive radio network utilizing software defined radio platform

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